Small-sample properties of maximum probability estimators

Lionel Weiss

Stochastic Processes and their Applications, 1983, vol. 14, issue 3, 267-277

Abstract: The theory of maximum probability estimation is predominantly asymptotic. In this paper it is shown that in many cases maximum probability estimators based on small samples are admissible for all practical purposes, in the sense that their expected gain function is arbitrarily close to the expected gain function of an admissible estimator.

Keywords: Estimation; efficiency; admissibility (search for similar items in EconPapers)
Date: 1983
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0304-4149(83)90004-2
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:14:y:1983:i:3:p:267-277

Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().